Intelligent Controller Time-to-Target Prediction Using Multiple Models
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Solution Overview
Problem
Intelligent controllers lack the capability to continuously and accurately calculate and display the time remaining until a control task is completed, especially in complex environments where multiple factors influence the control parameters, such as temperature in smart-home systems.
Innovation Solution
The implementation of intelligent controllers that use multiple models, including global and local models, to predict the time remaining until specified parameters are reached, by collecting data and generating parameterized plots to estimate and display this time, with features like automated control-schedule learning and adaptive feedback loops.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional control systems are used, then the system structure is simple, but the capability to continuously calculate and display time remaining until target state is lacking
Solution Approach 1:
The controller is divided into distinct functional modules: a data collection module that gathers sensor data, a model construction module that builds mathematical models from collected data, and a time prediction module that calculates time remaining using the models. This segmentation allows the complex functionality to be implemented in a structured, manageable way while maintaining accuracy.
Solution Approach 2:
The system performs preliminary data collection and model construction before the actual time remaining calculation is needed. By continuously gathering sensor data and pre-building mathematical models during normal operation, the system prepares prediction capabilities in advance, enabling accurate time remaining calculations without adding complexity to the real-time control path.
2Measurement precision
If multiple models are used for prediction, then the measurement precision of time remaining is improved, but the device complexity increases
Solution Approach 1:
The system automatically collects sensor data, constructs mathematical models, and performs time remaining calculations without requiring manual intervention. The controller autonomously manages the entire prediction process, from data gathering through model building to time estimation, reducing the operational complexity despite using multiple models.
Solution Approach 2:
The system continuously monitors actual system behavior and uses this feedback to refine and update the mathematical models. By comparing predicted time remaining with actual elapsed time and adjusting models accordingly, the system maintains high prediction accuracy while adapting to changing conditions, thereby managing model complexity dynamically.
3Reliability
If continuous data collection and model updating is performed, then the reliability of time projection is improved, but the use of energy increases
Solution Approach 1:
Instead of continuously updating models without interruption, the system performs data collection and model updating at periodic intervals. This approach maintains reliable time projections by regularly refreshing the models with current data while reducing energy consumption by allowing the controller to enter low-power states between update cycles.
Data Source
AI summary
The current application is directed to intelligent controllers that continuously, periodically, or intermittently calculate and display the time remaining until a control task is projected to be completed by the intelligent controller. In general, the intelligent controller employs multiple different models for the time behavior of one or more parameters or characteristics within a region or volume affected by one or more devices, systems, or other entities controlled by the intelligent controller. The intelligent controller collects data, over time, from which the models are constructed and uses the models to predict the time remaining until one or more characteristics or parameters of the region or volume reaches one or more specified values as a result of intelligent controller control of one or more devices, systems, or other entities.